Oscillatory combustion in rockets Semiannual report, 1 Jun. - 31 Nov. 1969

Droplet vaporization in region of critical point in flowing stream and stagnant gas at high pressures, and varying temperature

Scaled dimension and nonuniform complexity

Resource-bounded dimension is a complexity-theoretic extension of classical Hausdorff dimension introduced by Lutz (2000) in order to investigate the fractal structure of sets that have resource-bounded measure 0. For example, while it has long been known that the Boolean circuit-size complexity class SIZE � α 2n n has measure 0 in ESPACE for all 0 ≤ α ≤ 1, we now know that SIZE � α 2n n has dimension α in ESPACE for all 0 ≤ α ≤ 1. The present paper furthers this program by developing a natural hierarchy of “rescaled” resource-bounded dimensions. For each integer i and each set X of decision problems, we define the ith-order dimension of X in suitable complexity classes. The 0th-order dimension is precisely the dimension of Hausdorff (1919) and Lutz (2000). Higher and lower orders are useful for various sets X. For example, we prove the following for 0 ≤ α ≤ 1 and any polynomial q(n) ≥ n2. 1. The class SIZE(2 αn) and the time- and space-bounded Kolmogorov complexity classes KT q (2 αn) and KS q (2 αn) have 1 st-order dimension α in ESPACE. 2. The classes SIZE(2nα), KT q (2nα), and KS q (2nα) have 2nd-order dimension α in ESPACE

Integrated CORBA scheduling and resource management for distributed real-time embedded systems

Integration of middleware scheduling and resource management services enables open distributed real-time embedded (DRE) applications to meet end-to-end quality of service (QoS) requirements in highly variable operating environments. This paper describes our research1] on integrating CORBA scheduling and resource management services, and presents experiments we conducted to validate and quantify the benefits of this integration. Our experimental results show that integrating distributed scheduling and resource management in middleware for open DRE systems can offer significant improvements in predictability. Specifically, integrating our stand-alone resource management service with a previously unmanaged experimental baseline application reduced the ratio of missed deadlines from 26% to 10%, and the same application performed even better under the control of integrated scheduling and resource management services, with a missed deadline ratio of only 1%. © 2005 IEEE